Student Teams Win Best Project Award

Two teams of students earned best project honors earlier this semester for capstone projects completed last fall in George Westinghouse Professor of ECE David Casasent's Digital Communications and Signal Processing course. In the class, groups of three students worked throughout the semester to identify a project of their own choosing and implemented it on real-time digital signal processing (DSP) hardware. The Best Project awards, judged and sponsored by DRS Signal Solutions Inc., recognize the best overall project developed during the semester. Last fall, students created projects so diverse and outstanding that two awards were presented.

In the first project, "Find My Face! Photo Album Auto-Tagging," ECE seniors Saurabh Sanghvi, Ping-Hsiu Hsieh and Maxwell Jordan developed a method to auto-tag their friends in photos on the social networking site Facebook. ("Tagging" is Facebookese for labeling friends in photos.) The project had two stages - face detection and face recognition. To detect faces, the team separated a color image into individual red, green and blue channels on the computer and sent this data to the hardware DSP. The DSP then detected the locations of the faces and eye pairs and sent the coordinates back to the PC. (The presence of eyes eliminates false face detections.) The students then used an algorithm that identified cropped face regions as either Facebook friends or non-friends.

In their project, "A Shot in the Dark: Acoustic Point-Source Localization of a Gunshot," seniors Pranay Jain, Arda Orhan and Oren Wright designed a system that can detect the position and presence of a gunshot using an array of microphones. While the concept wasn't new, Jain, Orhan and Wright were the first ECE students to successfully pull it off in Casasent's class. Critical steps in their implementation solution included real-time source detection and accurate estimation of time delays between microphones. The former necessitated real-time sampling of four microphones, which the group accomplished with DSP external hardware used in conjunction with the course's Texas Instruments C67 DSP Starter Kit. The system first sampled and filtered incoming sound in real-time to detect the gunshot. Once the shot was detected, signal data was sent to a two-stage localization algorithm to determine the location of the shot. Time delay estimates between each microphone were then computed using a generalized cross-correlation algorithm, and these estimates were used to compute a near-field solution using the Gillette-Silverman algorithm. They then determined a far-field solution and compared it to the near-field results.

"The students challenged themselves with projects that contained many complex problems that engineers face every day," said Michael Kessler, a software engineer with DRS who helped judge the projects. "Each team used similar techniques we use at DRS to solve our own problems until they had a viable solution. They also leaned heavily on the labs taught by Dr. Casasent during the semester."